Development of Measurement Methods for Testing of Hydrokinetic Devices to Evaluate the Environmental Effect on Local Substrate

Modifications and upgrades to the hydraulic flume facility in the Environmental Fluid Mechanics and Hydraulics Laboratory (EFM&H) at Bucknell University are described. These changes enable small-scale testing of model marine hydrokinetic(MHK) devices. The design of the experimental platform provides a controlled environment for testing of model MHK devices to determine their effect on localsubstrate. Specifically, the effects being studied are scour and erosion around a cylindrical support structure and deposition of sediment downstream from the device.

DESIGN OF A LIQUID FUEL INJECTOR FOR ALTERNATIVE FUEL STUDIES IN AN ATMOSPHERIC MODEL GAS TURBINE COMBUSTOR

A new liquid-fuel injector was designed for use in the atmospheric-pressure, model gas turbine combustor in Bucknell University’s Combustion Research Laboratory during alternative fuel testing. The current liquid-fuel injector requires a higher-than-desired pressure drop and volumetric flow rate to provide proper atomization of liquid fuels. An air-blast atomizer type of fuel injector was chosen and an experiment utilizing water as the working fluid was performed on a variable-geometry prototype. Visualization of the spray pattern was achieved through photography and the pressure drop was measured as a function of the required operating parameters. Experimental correlations were used to estimate droplet sizes over flow conditions similar to that which would be experienced in the actual combustor. The results of this experiment were used to select the desired geometric parameters for the proposed final injector design and a CAD model was generated. Eventually, the new injector will be fabricated and tested to provide final validation of the design prior to use in the combustion test apparatus.

Assessment Of Dynamic Properties Of A Crowd Model For Human-Structure Interaction Modeling

As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.